Google has launched an exciting new initiative- a set of open classes to expose people to the information and tools necessary to succeed within the ever-growing era of generative AI. Because technology continuously improves the generative aspect of AI across industries, Google must employ qualified professionals to work with this tool. We are witnessing an attempt, shown by Mirasys India, to change the paradigm and actually advance learners and future masters of artificial intelligence.
Here’s a breakdown of the ten courses Google is offering:
1. Introduction to Generative AI:
Duration: 45 minutes
Description: This entry-level course defines generative AI, and explicates and illustrates its utility compared to ordinary machine learning. It also covers frameworks for developing generative AI applications using Google tools.
2. Introduction to Large Language Models:
Duration: 45 minutes
Description: Bridging the gap between models and capability awareness- Large language models (LLMs), their applications, and the value added by prompt tuning. It also involves the Google Web App tools for developing generative artificial intelligence applications.
3. Introduction to Responsible AI:
Description: This is why we have to talk about responsible AI, why Google tries to follow those principles and examine the seven AI principles that Google follows.
4. Generative AI Fundamentals:
Description: To earn a skill badge, you can finish Generative AI, Large Language Models, and Responsible AI courses. This is the basic level of generative AI, proving that you understand the fundamentals of this industry.
5. Introduction to Image Generation:
Description: Under this course, diffusion models are discussed which aids in generating images under the category of machine learning model. Here, you will learn about those models’ theories and how you can implement them using Vertex AI.
6. Encoder-Decoder Architecture:
Description: Explore the encoder-decoder approach used in various applications, starting from the WMT12 machine translation contest entries and including text summarization. The course provides a practical session in which you will develop a small poetry generation model using TensorFlow.
7. Attention Mechanism:
Description: Look through the previously mentioned attention mechanism that allows deep learning networks to pay more attention to some segments of an input sequence filling the need in such tasks as translation and text summarization.
8. Transformer Models and BERT Model:
Description: After a brief study of the Transformer structure and BERT model, which are at the core of many complex AI operations. Understanding how these models work and where they can be used for applications such as text classification or question answering.
9. Create Image Captioning Models:
Description: This course prepares you for building image captioning models through the application of Deep Learning. By the end of this module, you will know what the model comprises and how to teach and fathom your own captioning systems.
10. Introduction to Generative AI Studio:
Description: Learn more about Generative AI Studio on Vertex AI, a developing tool for generative AI models. This course comes with demos and knowledge checks to help you check that you have understood what has been taught.
Upon completing these courses, learners can avail themselves of a ‘Completion Badge’ from Google Cloud, which acknowledges learners’ mastery of generative AI. This badge proves their skill and knowledge as M2 patients with this emerging sub-specialty.
In a world where cutting-edge technology is at the forefront of development, these courses provide a unique chance to begin a gratifying career in generative AI. Therefore, use this opportunity that offers free education resources and helps pull the lever of artificial intelligence.
